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Paper Citation Record · LEDGER

Solver-Integrated Adversarial Attacking and Training of Neural Operators

As of 23 August 2026, this Paper Citation Record lists 88 of 88 outbound references and 0 inbound Pith citation observations for arXiv:2510.18989.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2510.18989 v3

Coverage vector

measured 88 of 88 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T08:50:06.930587Z

measured 88 of 88 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

88 of 88 outbound references displayed

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Outbound references

Observation b69c19a4-59a2-42b2-a279-17b63f109443 · outbound

This paper cites Wikipedia, 2025.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Wikipedia, 2025

Reference 1

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Observation 4fe03df6-9260-4f63-8b6b-592983ca6ae5 · outbound

This paper cites Wikipedia, 2025.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Wikipedia, 2025

Reference 2

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Observation 5ac94912-a26f-4654-92aa-901dde772b82 · outbound

This paper cites Evaluating the Adversarial Robustness for Fourier Neural Operators.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Evaluating the Adversarial Robustness for Fourier Neural Operators

Reference 3

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Observation 92501d2f-ade8-46e7-8c67-3ae6ab2e0341 · outbound

This paper cites Implicit Neural Differential Model for Spatiotemporal Dynamics.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Implicit Neural Differential Model for Spatiotemporal Dynamics

Reference 4

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Observation 28c9486b-1ac6-42ce-829b-abd499c6eb8d · outbound

This paper cites Differentiable programming across the PDE and Machine Learning barrier.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Differentiable programming across the PDE and Machine Learning barrier

Reference 5

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Observation 94a3efe0-f3a5-42c4-a29d-ce1c8d8c1565 · outbound

This paper cites Dedalus: A Flexible Framework for Numerical Simulations with Spectral Methods.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Dedalus: A Flexible Framework for Numerical Simulations with Spectral Methods

Reference 6

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Observation 41f55519-840b-412c-8264-52b3d6c7e893 · outbound

This paper cites Canuto, M.Y.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Canuto, M.Y

Reference 7

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Observation 5c10ed50-406f-4356-9c6e-e2d0f9af26da · outbound

This paper cites Clercx et al.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Clercx et al

Reference 8

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Observation 08ab42c0-a163-4380-959d-0fe4fb64b66d · outbound

This paper cites Soft-DTW: a differentiable loss function for time-series.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Soft-DTW: a differentiable loss function for time-series

Reference 9

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Observation 4455aba4-e965-4d3c-87f0-4e8bea0af229 · outbound

This paper cites Soft-dtw: a differentiable loss function for time-series.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Soft-dtw: a differentiable loss function for time-series

Reference 10

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Observation 9e4bb786-5ac3-47b0-8593-0e33a30edc89 · outbound

This paper cites Physics-informed re- duced order modeling of time-dependent pdes via differentiable solvers.arXiv preprint arXiv:2505.14595, 2025.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Physics-informed re- duced order modeling of time-dependent pdes via differentiable solvers.arXiv preprint arXiv:2505.14595, 2025

Reference 11

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Observation 1ce3fb78-7d98-461a-81e1-d0c47ff1c449 · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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Observation 79d5c7aa-d57a-4587-a8bb-425f281088c6 · outbound

This paper cites The kernel cookbook: Advice on covariance functions, 2014.

Solver-Integrated Adversarial Attacking and Training of Neural Operators The kernel cookbook: Advice on covariance functions, 2014

Reference 13

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Observation b4758c7d-b720-4c3e-8e5e-e95eeaf481b4 · outbound

This paper cites Fourier series representation of periodic signals.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Fourier series representation of periodic signals

Reference 14

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Solver-Integrated Adversarial Attacking and Training of Neural Operators GitHub / open source

Reference 15

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Observation 57fbfe79-6651-40c6-9cd9-c716fcaef677 · outbound

This paper cites Advanced gaussian processes (scribed notes, lecture 21).

Solver-Integrated Adversarial Attacking and Training of Neural Operators Advanced gaussian processes (scribed notes, lecture 21)

Reference 16

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Observation 1ee0d7f3-00c9-44bd-b9fa-d7a60fcd8f02 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Explaining and Harnessing Adversarial Examples

Reference 17

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Observation ed5f3261-862a-4d96-8e90-cf12cbbeb768 · outbound

This paper cites Discrete fourier transform and wavelet transforms (math 357 notes).

Solver-Integrated Adversarial Attacking and Training of Neural Operators Discrete fourier transform and wavelet transforms (math 357 notes)

Reference 18

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Observation 4fada03e-eaed-4ca0-8d17-ef6115cca72c · outbound

This paper cites Finite fourier transform, circulant matrices, and the fast fourier transform.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Finite fourier transform, circulant matrices, and the fast fourier transform

Reference 19

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Observation cd5d8ff7-7009-41a1-85d3-ed0d3533e26c · outbound

This paper cites Knowledge Distillation: A Survey.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Knowledge Distillation: A Survey

Reference 20

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Observation b8bf3f91-566c-4c88-bfac-111db1936173 · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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This paper cites A review: Applications of the spectral finite element method.Archives of Computational Methods in Engineering, 2023.

Solver-Integrated Adversarial Attacking and Training of Neural Operators A review: Applications of the spectral finite element method.Archives of Computational Methods in Engineering, 2023

Reference 22

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Spectral kernels (gpss 2021)

Reference 23

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Observation 3e5be8b6-c9f8-41df-adc5-10235593ea21 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Distilling the Knowledge in a Neural Network

Reference 24

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Observation 29a55a19-b8bf-44e5-8154-c34638ac0834 · outbound

This paper cites Hou and Ruo Li.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Hou and Ruo Li

Reference 25

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Observation 3304c5e5-42c1-436f-b64f-b809f561878e · outbound

This paper cites Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching

Reference 26

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This paper cites Unsupervised learning of full-waveform inversion: Connecting cnn and partial differential equation in a loop.Preprint / Conference (ICLR), 2022.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Unsupervised learning of full-waveform inversion: Connecting cnn and partial differential equation in a loop.Preprint / Conference (ICLR), 2022

Reference 27

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Solver-Integrated Adversarial Attacking and Training of Neural Operators , and Youzuo Lin

Reference 28

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This paper cites Perceptual losses for real-time style transfer and super-resolution.European Conference on Computer Vision (ECCV) Workshops, 2016.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Perceptual losses for real-time style transfer and super-resolution.European Conference on Computer Vision (ECCV) Workshops, 2016

Reference 29

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Cambridge University Press, 3rd edition, 2004

Reference 30

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Observation 97bbe2e8-3fc8-4888-a634-8adfa1117f27 · outbound

This paper cites Elastic image matching is np-complete.Pattern Recognition Letters, 24(1-3):445–453, 2003.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Elastic image matching is np-complete.Pattern Recognition Letters, 24(1-3):445–453, 2003

Reference 31

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Observation f3f21816-d645-4da2-be16-cb7221de2849 · outbound

This paper cites Exponax: Fourier spectral etdrk time-steppers in jax.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Exponax: Fourier spectral etdrk time-steppers in jax

Reference 32

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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This paper cites A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models.

Solver-Integrated Adversarial Attacking and Training of Neural Operators A Selective Survey on Versatile Knowledge Distillation Paradigm for Neural Network Models

Reference 34

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Laga and W

Reference 35

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Direct image matching by dynamic warping

Reference 36

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This paper cites Adversarial training for physics-informed neural networks (at-pinns), 2023.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Adversarial training for physics-informed neural networks (at-pinns), 2023

Reference 38

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Observation d715fdd0-ce10-4f11-8c6e-60b34bc602fc · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Fourier Neural Operator for Parametric Partial Differential Equations

Reference 40

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Observation 85a07042-a76e-4497-98d1-c61f4e0dbe2a · outbound

This paper cites Fourier neural operator with learned deformations for pdes on general geometries.Journal of Machine Learning Research, 2023.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Fourier neural operator with learned deformations for pdes on general geometries.Journal of Machine Learning Research, 2023

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source=pdf_text observed=2026-08-04T08:50:01.288235Z digest=sha256:0c551dca2c657a7ec49ad9fcf8833e337d0d2eb8296ed03ce981402aa3666e60

Observation 087a30da-8a8a-4eff-84fa-2cf6cd43248a · outbound

This paper cites Adaptive Movement Sampling Physics-Informed Residual Network (AM-PIRN) for Solving Nonlinear Option Pricing models.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Adaptive Movement Sampling Physics-Informed Residual Network (AM-PIRN) for Solving Nonlinear Option Pricing models

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source=pdf_text observed=2026-08-04T08:50:01.394086Z digest=sha256:d78b14bb8bca14a180cdb20f801f1935df4968d9305c5923092534617ca41afe

Observation 64076de2-2aaa-4106-bd44-a87318f22254 · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

Solver-Integrated Adversarial Attacking and Training of Neural Operators DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

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Observation f8a30806-0739-4b81-84bd-ef2076743c92 · outbound

This paper cites Karniadakis.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Karniadakis

Reference 45

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source=pdf_text observed=2026-08-04T08:50:01.770848Z digest=sha256:93ac3d7fb13ebbfa5859a8154ebd6befcba4f452de8b7e8b4a0408f011fdd1a8

Observation c49d35d9-97f4-4ff2-ad3e-b3cde096b241 · outbound

This paper cites Hilbert $C^*$-module independence.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Hilbert $C^*$-module independence

Reference 46

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Observation 0232b2ec-9492-4d9b-86f8-b61d864ff6cc · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 47

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source=pdf_text observed=2026-08-04T08:50:01.910950Z digest=sha256:b7319d8abdc406e138d6acf45bd500be4f9014d4b9ea419cc56e45b3d5887f90

Observation a56e6be4-cae2-49b8-99d5-8812d3247fb1 · outbound

This paper cites To- wards deep learning models resistant to adversarial attacks.

Solver-Integrated Adversarial Attacking and Training of Neural Operators To- wards deep learning models resistant to adversarial attacks

Reference 48

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Observation 21f11ee0-c70c-4c02-9752-4e9c22912ffc · outbound

This paper cites Majda and Andrea L.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Majda and Andrea L

Reference 49

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source=pdf_text observed=2026-08-04T08:50:02.108155Z digest=sha256:0b0a425c1671d52a49f161f31d3c8994d6d4fb4ec97984f1d022b886a9f82531

Observation 14b777e0-3d9d-421f-b3d5-598557a10ff2 · outbound

This paper cites Giometto, Marc B.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Giometto, Marc B

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source=pdf_text observed=2026-08-04T08:50:02.193675Z digest=sha256:b27123cc33044d63eb8bbf5c81b37c05c8c47eb18a5de5115bb93b3f32a0ceab

Observation 0c42672e-b966-4c84-95be-b718c3b89872 · outbound

This paper cites Circulant matrices.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Circulant matrices

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source=pdf_text observed=2026-08-04T08:50:02.250825Z digest=sha256:90fa2b585b25b2e2238f33fe38178cb31ed7d30b4f972a7fe8c9981e11991bc8

Observation 8e6f3a96-71f3-4f74-964d-a0f9af0cea50 · outbound

This paper cites Molenaar.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Molenaar

Reference 52

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source=pdf_text observed=2026-08-04T08:50:02.418335Z digest=sha256:5d3d4f8e6ca4fbc309f7aa50f8d34aabb4ef5024f20b1e95381835caf75cfff4

Observation a08735d3-66f9-4ec6-b1df-fb281f0d2564 · outbound

This paper cites Gladstone, and Hadi Meidani.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Gladstone, and Hadi Meidani

Reference 53

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source=pdf_text observed=2026-08-04T08:50:02.483383Z digest=sha256:0516288392fbb3edf7f256f71718f9e3e0d76f9875565667fc0d9292c506dcb2

Observation 1395c094-1794-454f-9b26-ec9ae3ef3729 · outbound

This paper cites Learning dtw global constraint for time series classification.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Learning dtw global constraint for time series classification

Reference 54

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Observation 23bcf278-18b8-43ab-96f6-31bc3ae911fc · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-04T08:50:02.737742Z digest=sha256:e7c626ec88474acc029ac98723d1dc59e8fe04cb891d615bff607f326cea210a

Observation caa17d88-13b2-4185-b17f-354ec7b56f34 · outbound

This paper cites AL-PINN: Active Learning-Driven Physics-Informed Neural Networks for Efficient Sample Selection in Solving Partial Differential Equations.

Solver-Integrated Adversarial Attacking and Training of Neural Operators AL-PINN: Active Learning-Driven Physics-Informed Neural Networks for Efficient Sample Selection in Solving Partial Differential Equations

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source=pdf_text observed=2026-08-04T08:50:02.845944Z digest=sha256:6e30c086e1d25dc889dea6fee6fb7070a2787b7ca1c4307f81e801cb7da805dd

Observation 5a2af5e7-87ce-452d-888b-a8fc1f8393de · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

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source=pdf_text observed=2026-08-04T08:50:03.019313Z digest=sha256:dfa774f6b28fc3a74893b9148bd2213a7407329d4147f4c8fb4863da108437db

Observation 34574005-86a5-421f-8cde-e9a40d985c47 · outbound

This paper cites Karniadakis.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Karniadakis

Reference 58

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source=pdf_text observed=2026-08-04T08:50:03.121190Z digest=sha256:dc15601a025fc7a474fd39d19d4ddc9b7a6971ea2d65ff4e57c9177286a0375e

Observation 9e1e3008-8f6e-406d-9130-f7ed05dc58ae · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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source=pdf_text observed=2026-08-04T08:50:03.185450Z digest=sha256:f7f427955a4473277003aa18a8bcc374d1a65e5c84fd93ca8e99c4f2ac6172cf

Observation 522ace5e-d383-4c61-a3fe-495c38cb04ac · outbound

This paper cites Williams.Gaussian Processes for Machine Learning.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Williams.Gaussian Processes for Machine Learning

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Observation 47c2ee0e-2ed4-4e4d-a5c9-9d67f5df1110 · outbound

This paper cites Fitnets: Hints for thin deep nets.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Fitnets: Hints for thin deep nets

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source=pdf_text observed=2026-08-04T08:50:03.310125Z digest=sha256:b2f91241e11facbe47cac130903868cf357bdc87a055e35bf3ee6412c835b3a8

Observation a123722e-3c79-45af-84fc-d313390c30e8 · outbound

This paper cites Wiley, 1990.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Wiley, 1990

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source=pdf_text observed=2026-08-04T08:50:03.379853Z digest=sha256:07556f25c7db1007211ad9a2548e516052ec4e5dc4f6cbbaf9be9dfbcce888c4

Observation f84a3b02-874d-476e-8ba4-cfea37fe3c4d · outbound

This paper cites Dynamic programming algorithm optimization for spoken word recog- nition.IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1):43–49, 1978.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Dynamic programming algorithm optimization for spoken word recog- nition.IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1):43–49, 1978

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source=pdf_text observed=2026-08-04T08:50:03.469168Z digest=sha256:60067fbb153c9e452cfb3f1ddd2ee39afd410e69ccb99e7841cbb1e592d2305f

Observation 42b1808f-e18a-4fe4-802f-d32e4fa07e55 · outbound

This paper cites Dynamic time warping algorithm review.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Dynamic time warping algorithm review

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Observation af7aac86-c95e-4858-bdd0-7bcd8d33e6e2 · outbound

This paper cites Discovering the fourier transform: A tutorial on circulant matrices, circular con- volution, and the dft.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Discovering the fourier transform: A tutorial on circulant matrices, circular con- volution, and the dft

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source=pdf_text observed=2026-08-04T08:50:03.712530Z digest=sha256:8e34e083f4be2679194a60b22d1df76ed1c33827061f2db4f63cd68dd12e2aa3

Observation 36b1e856-f75b-4e70-905a-cd20e3fe4482 · outbound

This paper cites Understanding gaussian process regression using the fourier transform, 2000.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Understanding gaussian process regression using the fourier transform, 2000

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source=pdf_text observed=2026-08-04T08:50:03.858332Z digest=sha256:4b468cc71eaaeff255eefe50de4d4b0f9fb8b9fd462288d6f0cf14f4d54f1751

Observation 3cfb60aa-50f9-4192-9b61-e6ae5795347a · outbound

This paper cites Fourier-spectral methods for navier–stokes equations in 2d.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Fourier-spectral methods for navier–stokes equations in 2d

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Observation 734f2627-1fbc-4af0-8990-51950e7e2799 · outbound

This paper cites Physics-based Deep Learning.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Physics-based Deep Learning

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Observation 048dc6e9-015c-4d5d-9e0c-160217531848 · outbound

This paper cites Trefethen.Spectral Methods in MATLAB.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Trefethen.Spectral Methods in MATLAB

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Observation 9f8133e2-a84f-4a14-b75c-cc1636a562be · outbound

This paper cites Physics-informed neural network with adaptive mesh refinement sampling.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Physics-informed neural network with adaptive mesh refinement sampling

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Observation 5284dedc-bd98-4fe6-8a29-8646ad682b70 · outbound

This paper cites Solver-in-the- loop: Learning from differentiable physics to interact with iterative pde-solvers.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Solver-in-the- loop: Learning from differentiable physics to interact with iterative pde-solvers

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Observation d193881c-4aea-4d81-abcf-1f31187a3ae4 · outbound

This paper cites Generalized harmonic analysis.Acta Mathematica, 1930.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Generalized harmonic analysis.Acta Mathematica, 1930

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Observation 4010bd97-746c-4001-bc63-ef38ab22f21a · outbound

This paper cites Gaussian Process Kernels for Pattern Discovery and Extrapolation.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Gaussian Process Kernels for Pattern Discovery and Extrapolation

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Observation 326a4580-a755-4cb2-8912-fb85f91ec84a · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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Observation 425a983a-6548-4f00-bed1-4d4fe4c33df2 · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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Observation 0d7d9ef1-e7c0-489c-8c62-e379708e9967 · outbound

This paper cites Wood and Grace Chan.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Wood and Grace Chan

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Observation 51f39edf-9d87-4c47-adc2-0b7aa1b39376 · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

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source=pdf_text observed=2026-08-04T08:50:05.572770Z digest=sha256:8a77a6a941efac44ed23f37247857c8d6072712875b43855e4d66f278f36c7cf

Observation c0caa0eb-383e-4a88-834b-29f698c9529b · outbound

This paper cites On the generalization properties of adversarial training.

Solver-Integrated Adversarial Attacking and Training of Neural Operators On the generalization properties of adversarial training

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source=pdf_text observed=2026-08-04T08:50:05.701143Z digest=sha256:1a7f4a67a1fc5b95c4870e8f317e2db5009bf12d0b85e809f05db67933080e08

Observation f2b37bb6-3bd1-45af-be88-52539bb68df8 · outbound

This paper cites Karniadakis.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Karniadakis

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source=pdf_text observed=2026-08-04T08:50:05.770740Z digest=sha256:54a0b46e38e014d9fe626e728dd42c8dbe04139b1b791537f01416fa51ddf610

Observation db1df7cc-d0b6-4eb2-9573-8dd13706fdf2 · outbound

This paper cites Karniadakis.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Karniadakis

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source=pdf_text observed=2026-08-04T08:50:05.877961Z digest=sha256:0ef6d259bf159bb50dbf493896190204e90b6cff1a306a49fc5fdeb8c92618e9

Observation 85e1e3a2-a73e-4c99-9015-6dc4e8b3f44a · outbound

This paper cites Adversarial Training: A Survey.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Adversarial Training: A Survey

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Observation 5c951f97-78c3-4a4e-8cf1-b276d1b81730 · outbound

This paper cites Improving generalization of adversarial training via robust critical fine-tuning.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Improving generalization of adversarial training via robust critical fine-tuning

Reference 83

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Observation 0ffc57b9-1bd5-4c30-9fa0-284fd11ea1f3 · outbound

This paper cites For FFT libraries using real-to-complex transforms (e.g.

Solver-Integrated Adversarial Attacking and Training of Neural Operators For FFT libraries using real-to-complex transforms (e.g

Reference 86

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Observation 910dec9c-b12d-4757-a5a3-80c34f9fd6df · outbound

This paper cites 2/3 rule):M(k x, ky) = 1 if|k x| ≤N 3 and|k y| ≤N 3 , else 0.

Solver-Integrated Adversarial Attacking and Training of Neural Operators 2/3 rule):M(k x, ky) = 1 if|k x| ≤N 3 and|k y| ≤N 3 , else 0

Reference 87

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Observation 79be1ece-1175-4bbf-a664-578a99087119 · outbound

This paper cites RBF kernel.

Solver-Integrated Adversarial Attacking and Training of Neural Operators RBF kernel

Reference 88

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Observation ad4f23f8-3b85-4ea2-b3e4-d40cfebe9ed6 · outbound

This paper cites an unresolved cited work.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 89

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Observation 6978b457-6323-4629-afa0-da4f05119ec6 · outbound

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Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 90

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Observation 3938ffee-22bf-488a-b458-441b77e7f63c · outbound

This paper cites an unresolved cited work.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 91

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Observation 63fad0eb-96af-4d93-a7ef-7e0ae098559c · outbound

This paper cites •Analogy with finite-dimensional Gaussian sampling.In finite-dimensional statistics, sampling a Gaussian vector with covarianceC=QΛQ T is done viaQΛ 1/2 z.

Solver-Integrated Adversarial Attacking and Training of Neural Operators •Analogy with finite-dimensional Gaussian sampling.In finite-dimensional statistics, sampling a Gaussian vector with covarianceC=QΛQ T is done viaQΛ 1/2 z

Reference 92

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Observation ef169d6a-40d6-4b89-bc99-f03bd71a7b95 · outbound

This paper cites an unresolved cited work.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 2011

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Observation 19deca6c-f009-497c-8077-ce072689bd26 · outbound

This paper cites an unresolved cited work.

Solver-Integrated Adversarial Attacking and Training of Neural Operators Unresolved cited work

Reference 2013

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